Online geometric reconstruction

Bernard Chazelle, C. Seshadhri

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

We investigate a new class of geometric problems based on the idea of online error correction. Suppose one is given access to a large geometric dataset though a query mechanism; for example, the dataset could be a terrain and a query might ask for the coordinates of a particular vertex or for the edges incident to it. Suppose, in addition, that the dataset satisfies some known structural property P (for example, monotonicity or convexity) but that, because of errors and noise, the queries occasionally provide answers that violate P. Can one design a filter that modifies the query's answers so that (i) the output satisfies P; (ii) the amount of data modification is minimized? We provide upper and lower bounds on the complexity of online reconstruction for convexity in 2D and 3D.

Original languageEnglish (US)
Article number14
JournalJournal of the ACM
Volume58
Issue number4
DOIs
StatePublished - Jul 1 2011

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Hardware and Architecture
  • Artificial Intelligence

Keywords

  • Computational geometry
  • Sublinear algorithms

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